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The Art and Science of User Engagement: Personalization and Recommendations in the OTT Era
Abstract
This chapter explores the importance of personalization and recommendation algorithms in OTT era, emphasizing their role in enhancing content discovery and customizing user experiences. Crucial techniques like collaborative filtering and content-based filtering underpin these algorithms, which ensues personalized user experiences. Recommendation algorithms shape media consumption patterns, content discovery, influencing user behavior, cross-platform consumption and binge-watching habits. This chapter also paid attention to acknowledging ethical considerations like privacy concerns and algorithmic bias. Additionally, it also explores the challenges and opportunities for content creators in catering to algorithmic preferences, along with significance of balancing effective ad targeting and user privacy in personalized advertising. Improving and assessing recommendation algorithms using different metrics and feedback loops is important, however future trends concentrate on contextual personalization and adaptive experiences, enhancing user's entertainment journey.
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